FIELD OF INVENTION
This invention relates to an improved system for the analysis and prediction of product demand.
For more efficient product planning in a retail environment given a plurality of products of short shelf life, a tendency exists toward resorting to production plans that are calculated on an infrequent basis. This basis is often daily at best and more often is based on an average for a given day of the week. This results in excessive product and waste or not enough product to meet customer demand. To expect a human being to calculate product demand on a more frequent basis such as hourly or every fifteen minutes would be impractical if not impossible.
In addition to the impracticality of computing product demand manually on a more frequent basis is the complexity introduced by different demand patterns for each day of the week and seasonality during the year. Customer foot traffic and product preferences are unique to each day of the week. These traffic patterns and preferences are further complicated by seasonality trends week by week throughout the year. Accommodating this level of complexity requires a unique solution to store the past-product demand by seasonality, day of the week, and time period during the day, for each of a plurality of products.
Another difficulty encountered once the past-product demand has been stored is the ability to deal with incomplete data from current time periods and to compare trends in just-completed time periods against preestimated demand in the same time periods in order to adjust near-future time periods accurately and with confidence. One method for making such comparisons and projections on other near-future periods is to take a simple positive or negative percentage of the trend of just-completed periods against preestimated periods and apply it to the remaining preestimated near future periods for the day. This method is unreliable given the many anomalies that can occur, for example, when a bus load of people arrives or an unusually large order is placed.